Evaluating AI productivity tools: A guide for IT teams

Tips and suggestions for choosing the right tools for your team.

Katy Turner

Product Marketing Manager at Coda

Evaluating AI productivity tools: A guide for IT teams

By Katy Turner

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IT Teams · 7 min read
When ChatGPT launched in November 2022, it took off like a rocket, gaining more than one million users within five days. Suddenly, generative AI was the hottest topic in tech, with teams around the globe wondering how to harness its capabilities to make their lives easier and their organizations more productive. With so many AI-enabled software solutions entering the market, IT departments found themselves overwhelmed with a new set of tool requests from across the company. However, bringing any new platform into an organization’s tech stack requires a rigorous evaluation process that balances the desire for cutting-edge tech with the need for security and compliance. So, what’s the best way for IT teams to assess potential AI-powered solutions? Here are some helpful tips and strategies for making the right decisions when it comes to adding AI productivity platforms to your company’s toolbox.

Understanding AI productivity tools.

 First off, some clarification: AI can refer to both “traditional” artificial intelligence and “generative” artificial intelligence. Traditional AI uses algorithms to analyze existing data and make predictions, while generative AI (like ChatGPT) creates entirely new content based on user-provided prompts. Whenever we refer to “AI” in this post, we’re talking about generative AI. An AI productivity tool is any piece of software that uses generative AI to help teams or individuals complete tasks faster and more accurately. Since the start of the AI boom, solutions have emerged to solve very specific workplace needs. Some of the most frequently-encountered solutions that IT teams need to evaluate include platforms for:
  • Writing assistance (generating content, proofreading, and editing).
  • Knowledge assistance (providing contextual information, answering questions, and delivering personalized recommendations).
  • Task assistance (scheduling, reminders, and task management).

What to consider when evaluating AI productivity tools.

 How can IT departments determine whether a specific AI productivity tool is right for their organization? Below, we’ll go through specific areas to take into account before making a final decision.

Data security and privacy.

 Your data is one of your company’s most important assets, so keeping it secure is your top priority. When assessing AI productivity tools, review their security and compliance certifications (if any) and protocols surrounding the use of customer data. Also, verify whether your data will be used to train the tool’s AI models.

Compatibility with existing systems and workflows.

 Whichever AI productivity tool you choose should, at the very least, be compatible with the software and systems your team already uses. Ideally, it shouldn’t even be a separate experience. The best AI productivity tools are readily available within the surface where your users spend most of their time—not in a separate tab. Why? Imagine you’re on a roll writing a new blog post but you have to interrupt your workflow to open another tool, get the content you need, and then copy/paste it back in. Instead, an AI assistant should be there on demand, right in your current workspace.

Ease of integration and implementation.

 IT teams have enough on their plates—there’s no need to add a cumbersome AI tool integration process to the to-do list. Before selecting a potential solution, estimate how long it would take to connect it to your company’s critical systems and workflows, then compare that timeline to that of other AI options. Also, remember that IT’s commitment to a new tool doesn’t stop at launch—usage monitoring, renewals, etc., are a long-term responsibility. The value needs to be greater than the time investment.

User interface and user experience.

 If you’re going to go through the trouble of bringing in a new tool, you want your team to actually use it. Strong UI/UX is a must for driving high levels of user adoption. After all, no one wants to spend their time working in a clunky, hard-to-navigate interface. A context-aware AI productivity tool (like Coda AI) is even more appealing, as it references the work your team is already doing when making suggestions or reacting to prompts.

Scalability and flexibility for future needs.

 As your organization grows, you’ll need a tool that can support you at scale, and that is flexible enough to handle new use cases and evolving team requirements. Don’t get stuck with a limited, single-use tool that only offers, say, writing assistance, when you hope to use it for task assistance down the line as well.

Evaluating AI productivity tools.

 We’ve gone through the “what” of assessing AI productivity solutions. Now let’s get into the “how.” Any AI assessment should include the following five steps.

1. Assess the tool’s functionality and features against specific use cases.

 How will your organizations primarily be using this tool? Writing assistance? A chatbot? Data analysis? Take advantage of any free trials or pilots to see if the platform you’re considering can handle the exact tasks it would be performing day to day.

2. Evaluate context awareness.

 The more context you give AI (about your brand voice, your organization, your products, etc.), the more useful its outputs will be. Consider what types of context your AI platform can leverage and whether it can easily reference your team’s past work. Context-aware AI tools, like Coda AI, have a shorter time-to-value than other options, as your team will spend less time editing/reviewing the results.

3. Seek user feedback and reviews.

 What are other companies in your industry saying about the platform? How have they leveraged it successfully (or unsuccessfully)? Read reviews from sites like G2 and Capterra, and after your pilot project/task, ask your end users about the pros and cons of their experience.

4. Compare pricing models and value for cost.

 Any AI productivity tool needs to fit into your company’s software/tech budget. For some companies, one-off pricing might make the most financial sense, while others may find subscription options more feasible. Plus, some AI tools are paid add-ons to other software, rather than separate solutions altogether. For example, if you have a Doc Maker license, Coda provides you with a pool of AI credits to use at no extra charge. Notion, however, has a mandatory add-on cost for those who want to explore AI use cases.

5. Evaluate the tool’s customer support and training resources.

 If you run into problems getting set up or down the road, how quickly will you be able to get help? How robust are the tool’s training programs or learning resources? Any platform you select should be able to support your users with knowledge and assistance both at the beginning of your journey and throughout its lifetime at your company. In our experience, the best way to find fair and accurate information about a tool’s customer service is by reading user reviews.

Incorporating this criteria.

The above evaluation steps are the minimum. You might need to establish additional assessment criteria for your own IT team. We also recommend setting guidelines around AI tool requests—who can make them, what info they should include, how to send them in, and estimated response timelines. You should also make how and where to provide feedback clear, as they pilot or use the tool for their workflows. etc.

Why IT teams choose Coda.

 Coda AI is our new AI-powered work assistant, and it’s already helping tens of thousands of teams, like Figma and Intercom, deliver impressive results. It is context-aware, scalable, flexible, and available where you work, not in a separate tab. In addition, it can be used for all three of the major AI workplace use cases: writing assistance, knowledge assistance, and task assistance. Also, Coda AI is secure: we don’t allow any AI third-party providers and contractors to use your data to train their own models, and we don’t use AI inputs or results from our enterprise customers to improve our AI functionality. Learn more about security at Coda. Beyond Coda’s AI capability, our platform is a powerful solution for IT teams, allowing them to better support their organization’s goals, cut software costs through tool consolidation, and accelerate IT transformation. For more information on Coda for IT, check out our Ultimate Coda Handbook for IT Teams.

Put AI to work for your IT org.

 New AI-enabled productivity software programs enter the market seemingly every day, which means IT teams have a big job deciding which is best for their company. By following the steps and advice above, you’ll be starting off on the right foot on your AI evaluation journey. And if Coda AI is on your list of options, here’s everything you need to know.
Learn more about Coda AI

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